Projective devices such as cameras, projectors and the like are used pervasively within the imaging industry. Projective devices are increasingly used in collections. For example, projectors are arranged in an array or other configuration to enable wide area display of image and video content onto surfaces of arbitrary shapes. Similarly, arrays of cameras have found application in computational cameras where the output of each camera is computed based on the total set of camera views captured. Such systems offer great scalability in that the systems can be added to in accordance with changing requirements or improving technology. Collective systems also offer redundancy which can improve reliability in the event of failure of a single device. Mixed collections of projective devices are also useful. One example is the automatic keystone correction of projector display where a camera is used to obtain a view of the projected image and image processing is used to pre-warp the projected image so that the projected image is displayed rectified to the projection surface.
A significant obstacle in the use of collections of projective devices is calibration of the collection to act as a single unit. While many techniques exist, most of the existing techniques place special constraints on the physical configuration of the collection and may require additional use of calibration aids. Requiring addition calibration aids creates an unacceptable technical obstacle to many end users and, as a result, such collections of projective devices must be installed and maintained by technical experts.
One known technique requires the user to establish point correspondences between the projective image planes of multiple projector devices manually. Given 2 overlapping projection areas, the user first manually chooses a point in the overlap region within the first projector image, and then manually searches and selects a corresponding point within the second projector image.
Another known system provides for automatic keystone correction of a single projector based on analysis of a camera image of the projection area. However, the exact relative pose of the camera and projector is required. If the camera and projector are present as separate physical objects then the relative pose must be determined through the use of charts or other calibration devices. The calibration would need to be performed each time the devices moved relative to each other. The resulting process can become cumbersome and unreliable for an end user.
Device calibration process typically results in several intrinsic parameters of the device. Intrinsic parameters include focal length, principal point, and lens distortion parameters. One known automatic projector calibration method minimises a cost function based on evaluation of circular point constraints in the image planes of three or more projectors. However, the method makes assumptions about the location of the principal point. The assumptions do not hold when the projector has lens shift capabilities which shift the position of the projector's principal point. Other methods rely on an initial projector calibration having been performed, which is not guaranteed in many situations. Yet other methods require multiple planar projection surfaces to be arranged in a known configuration.